| Name | dat |
| Number of rows | 500 |
| Number of columns | 5 |
| _______________________ | |
| Column type frequency: | |
| numeric | 5 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| V1 | 0 | 1 | 8.13 | 9.82 | -17.28 | 0.52 | 7.01 | 14.79 | 45.67 | ▁▇▆▂▁ |
| V2 | 0 | 1 | -0.18 | 11.38 | -43.28 | -7.67 | 0.96 | 6.81 | 39.61 | ▁▂▇▃▁ |
| V3 | 0 | 1 | 0.33 | 9.75 | -33.39 | -6.38 | 0.65 | 7.29 | 30.54 | ▁▃▇▅▁ |
| V4 | 0 | 1 | 0.44 | 10.05 | -28.53 | -7.79 | 0.59 | 9.00 | 28.57 | ▁▆▇▆▁ |
| V5 | 0 | 1 | 0.39 | 10.36 | -30.85 | -8.61 | 0.68 | 8.89 | 29.29 | ▁▆▇▇▁ |
column means:
## V1 V2 V3 V4 V5
## 0.43457 1.31718 -0.04885 9.96364 9.92084
column ggcorr:
column means:
## V1 V2 V3 V4 V5
## 10.0844 -0.2670 0.1087 0.5503 0.5052
column ggcorr:
column means:
## V1 V2 V3 V4 V5
## 9.6498 -1.5842 0.1575 -9.4134 -9.4156
column ggcorr:
## Call:
## lda(dat, grouping = clas)
##
## Prior probabilities of groups:
## cl b cl c cl a
## 0.1 0.8 0.1
##
## Group means:
## V1 V2 V3 V4 V5
## cl b 0.4346 1.317 -0.04885 9.9636 9.9208
## cl c 10.0844 -0.267 0.10867 0.5503 0.5052
## cl a 0.1503 -1.007 2.47480 -9.9307 -10.0203
##
## Coefficients of linear discriminants:
## LD1 LD2
## V1 -0.007472 -0.110349
## V2 -0.006776 0.002333
## V3 0.008456 0.016209
## V4 -0.080285 0.008986
## V5 -0.075444 0.003564
##
## Proportion of trace:
## LD1 LD2
## 0.7208 0.2792
## Standard deviations (1, .., p=5):
## [1] 11.415 11.036 10.021 9.543 9.265
##
## Rotation (n x k) = (5 x 5):
## PC1 PC2 PC3 PC4 PC5
## V1 -0.04224 0.04756 -0.789633 -0.50294 0.3457
## V2 0.98593 -0.12357 0.007765 -0.03285 0.1074
## V3 0.02224 -0.17544 -0.570261 0.79283 -0.1223
## V4 0.15389 0.60934 -0.209137 -0.13362 -0.7372
## V5 0.04459 0.76184 0.086507 0.31551 0.5573
Original variable cluster seperation:
Original vs MMP cluster seperation:
MMP cluster seperation: